THE RELATIONSHIP OF LOCAL PUBLIC EXPENDITURES AND
RESIDENTIAL PROPERTY VALUES IN MASSACHUSETTES TOWNS
by
John Benjamin Fleeman
A. B., Bowdoin College,
Economics and Government
(1978)
Master of Science in Management,
Florida
International University
(1981)
Submitted to the Department of Architecture in Partial
Fulfillment of the Requirements for the Degree of
MASTER OF SCIENCE
in Real Estate Development
at the
Massachusetts Institute of Technology
September, 1990
(c) John Benjamin Fleeman
The author hereby grants to MIT permission to reproduce and
to distribute copies of this thesis document in whole or in
part.
Signature of Author
7
of Archicur
July 30, 1990
'~IM~artment
Certified by
Mard A. Louargaind
Lecturer, Department of Urban Studies
Thesis Supervisor
Accepted by______________
Glori'19Shuck
Chairperson
Interdepartmental Degree Program in Real Estate Development
MASSACHUSETTS INSTITUTE
OF TECHNPr
Afy
SEP 19 1990
LIBRARIES
THE RELATIONSHIP OF LOCAL PUBLIC EXPENDITURES AND
RESIDENTIAL PROPERTY VALUES IN MASSACHUSETTS TOWNS
by
John Benjamin Fleeman
Submitted to the Department of Architecture on July 30,
1990 in partial fulfillment of the requirements for the
degree of Master of Science in Real Estate Development
ABSTRACT
This is a study of the relationship between local
public expenditures and single family residential property
values in several Massachusetts towns. The majority of the
literature regarding the general relationship of public
expenditures and property values indicates that the value
of public services is capitalized into higher home prices,
while higher property tax rates are capitalized into lower
home prices.
Data
regarding
actual
home sales
and
public
expenditures in ten towns are used in a multiple regression
model to test this hypothesis. The results indicate a
positive relationship between home values and police and
education expenditures, but also, a positive relationship
between home values and tax rates. Closer scrutiny reveals
that other factors positively correlated with both tax
rates and home values, such as restrictive zoning and per
capita income, lead to a positive relationship between tax
rates and home values, contrary to the expectations of an
"all else equal" model.
Thesis supervisor: Marc A. Louargand, Ph.D.
Lecturer
Department of Urban Studies and Planning
ACKNOWLEDGEMENTS
I would like to thank my wife, Diana, for the love,
support and encouragement she has given me not only during
the production of this thesis, but also throughout more
than six years of marriage.
Thanks also go to our
daughter, Rebecca, who brought both of us great joy during
this first year of her life. Finally, to my advisor, Marc
Louargand, for his patient and positive guidance through
the thesis process.
John B.Fleeman
Cambridge,MA
July, 1990
TABLE OF CONTENTS
I )
INTRODUCTION.......................................
5
II) LITERATURE REVIEW...................................12
III) THE MODEL..........................................29
IV)
RESULTS, INTERPRETATION AND DISCUSSION.............41
V)
CONCLUSIONS........................................ 48
VI)
APPENDIX I......................................... 51
VII) APPENDIX II........................................60
VII) REFERENCES......................................... 62
LIST OF TABLES
1. Summary of Expected Signs............................41
2. Regression Results...................................42
I) INTRODUCTION
This is a study of the relationship between local
single family residential property
public expenditures and
values in
several Massachusetts towns.
of
number
studies
the
provided
services
reflect that
study
draws
relationship,
past
which
and
governments
local
for homes
provide more public services.
in
few variables
a
have
hypothesis that people
previous work
from
and adds
by
have been a
paying higher prices
valuation by
located in communities which
This
the
in
confirm or reject the
attempted to
value
conducted
There
the
analyzing
not observed
in
public services
in
previous studies.
reflection of
The
higher home
such
The
considering a
provides a
consumers
among housing
indifferent
a relatively
Further, assume that
stock
both
difference between
Suppose
are
other is the availability
must
be
a family
is
A, which
low level
of public
all aspects of the housing
identical
living in
of
services, and
level of public
relatively high
towns
housing
choosing between Town
services.
in
a condition
in
of
choices.
move and is
which provides
capitalization of
to as a
is that
concept
equilibrium,
economic
value of
prices is referred
services.
Town B,
the
so
one town
that
the
as opposed
of public services.
only
to the
Given those
circumstances, it is clear that the family will choose Town
A and enjoy
the greater
availability of
incurring any additional cost.
services without
On
a
broader
scale,
this will
prospective
homebuyer choosing
Eventually,
in
the absence
sites, everybody
the consumer is indifferent
between
the towns
Thus,
public services
additional
available
increases in
At what
stop?
process
up until housing in Town
housing in Town
B that
between living in lower priced
and higher priced housing in
the housing
reflect how
will
towns.
However, scarcity
bidding-up
housing in low-service Town B
A.
A.
every
these two
for housing
enough relative to
high-service Town
of
scarcity of
a
Theoretically, prices will be bid
A is expensive
true
housing will be bid up.
this
will
level
of
as the demand
Town A, the price of such
price
between
would live in Town
factor, and
is a
be
consumers value
available in
value of the additional services
price difference
Town A,
the
and the
is said to be capitalized
into the housing prices in Town A.
The
problem
attempting
of
to
demonstrate
capitalization with empirical data is that far more factors
than just
prices.
the provision of public
The
differences,
such
theory
but in
described above
reality, it
uniformity among
the purchase
with issues
services affect housing
relating to
is difficult
housing choices.
of a home, consumers
the site,
their place(s) of employment
assumes
away
such
to imagine
When considering
typically are concerned
such as
distance from
and neighborhood security, as
well as issues relating to the dwelling itself, such as the
size of
the house, its
age, and style.
explain the relationship of
In
attempting to
housing prices to local public
expenditures, a
factors
study must
so that
hold constant for
they will
not bias
these other
the estimate
of how
public services relate to property values.
The most common approach to this problem is the use of
hedonic
pricing
concept
that the
models.
Such
commodity under
case, housing) is really
(more accurately, a
are
based on
consideration (in
this
The market price of a house
set of housing services
dwelling)
the
a collection of commodities, each
of which has a distinct value.
particular
models
is the
sum
of
provided by a
the prices
individual commodities (see Goodman [2],
of
the
Griliches [3],
and
Sullivan [15]).
By collecting data regarding these various
components
housing
of
statistical
services
technique of
and
the
multiple linear
use
of
the
regression, the
influence of each commodity on the overall price of housing
services can be estimated*.
For example, if we were
vary solely
with square
to assume that housing prices
footage, distance to
Business District (CBD) and the
collect
data
regarding
the Central
age of the house, we would
those independent
variables
and
estimate a linear relationship of the form:
P =
a + bX 1
-
cX
2
-
dX
3
where P is the price of a house and a is the intercept (the
value of P when the
independent variables are zero),
X1 is
square footage, X 2 is distance from
the CBD, X 3 is the age
------------------------------------------------------
* -
It is assumed that the
reader has a basic knowledge of
multiple linear regression and the interpretation
statistical significance of equation coefficients.
of the
of the house, and b, c and d are the coefficients
of X, X 2
and X3 ,
respectively.
Each coefficient
relates the
expected change in
independent
P for a one unit change
variable,
assuming
variables in the equation
sign for
and price.
square footage results
negative signs for c
other
are held constant.
b implies a positive
footage (Xj)
all
That
in an increase by b
increase in
in price.
The
and d indicate negative relationships
price.
unit
decreases by c,
The positive
is, a one unit
from the CBD (X2 ) and
a
independent
relationship between square
between both distance
For
in its related
one
increase
in
age (X3)
with
distance,
and for a one unit increase
price
in age, price
decreases by d.
Hedonic pricing models
estimate prices for
a collection
of
utilize regression analysis to
heterogeneous commodities comprised of
distinct
commodities.
The
independent
variables are the distinct commodities and the coefficients
of each variable
distinct
are the indicators of how a
commodity
commodity.
Thus,
magnitude and
affects
the
the models
price
attempt
direction of each
of
to
unit of that
the
overall
show both
variable by the
the
size and
sign of the coefficient.
This
study
is
concerned
relationship
between
single-family
residential
local
hedonic pricing model which
local public expenditures
with
public
property
explaining
the
expenditures
and
values,
and
uses
a
includes several categories of
as independent variables.
independent variables thought to
Other
have a significant impact
upon
single-family
variable) are
linear
residential
values
analysis
is
used
dependent
and then multiple
included in the database,
regression
(the
to
determine
what
relationship exists.
From
a
standard
hypothesis (HO)
statistics
is that local expenditures
single-family residential
upon
coefficients
perspective,
for
the
public
statistically significantly
property
the
null
have no effect
values.
expenditure
If
the
variables
are
different from zero,
the null
hypothesis is rejected.
Taking a
less rigorous
that there is a
approach, the
expectation is
positive relationship between local public
expenditures and single-family residential property values.
As discussed
in our initial example
seems reasonable to expect that
pay more for
more
than
houses if the houses were
B, it
people would be willing to
houses located in a
public services
of Towns A and
community which provides
they would
pay
for the
same
located in a community providing
fewer public services.
Another factor
effect
of
property
in the
capitalization process
taxes.
Lower
property
is the
taxes
are
presumed to be capitalized, yielding higher housing prices.
If a homebuyer is faced with a choice between two identical
homes
in
the
property tax
same
location which
burden, the
differ
buyer should
only
be willing
in
the
to pay
more for the home for which taxes are lower.
However, property taxes are usually the main source of
revenue for
local governments.
Thus, in
order to provide
public services,
property
taxes.
local governments must be
To the
extent
demanded, it is likely that
Thus,
one
might
expect
that
able to impose
more services
are
property taxes will be higher.
to observe
opposing
forces
of
capitalization - a negative relationship between prices and
tax rates
and a
positive relationship between
public expenditures.
The net result will
prices and
depend upon how
homebuyers view the benefits of public services relative to
the
cost of
the
greater than
If not,
taxes.
the costs,
viewed as
the
perceived benefits
housing prices should
the net result
taxes are
If
be higher.
will be lower housing
a direct
are
prices.
payment, equivalent
If
to the
value of the services, the net effect is neutral.
Some of the literature discussed in Section II of this
study
takes
the
view
that
equilibrium, taxes and public
since taxes are viewed as
in
a
state
of
long-run
services are not capitalized
the pricing mechanism for public
services, and thus, the two do not affect housing prices.
Since
percentage
property
of
taxes
housing
generally greater upon
values,
$1,500 of
$90,000 house
and another
town.
$10,000 lives
Further suppose
increase by
The
$90
increase
their
levied
income
as
effect
household with
in a $250,000
that
a
is
Suppose a
discretionary income lives
10%, from $10 per
$1,000 in value.
generally
lower-income households.
household with
income of
are
in a
a discretionary
house in
property taxes
the same
in the
$1,000 in value to
town
$11 per
The family with the $90,000 home sees its
represents 6.0%
10
of
its
discretionary
income.
The family
with the $250,000 home
rise from
$2,500 to $2,750.
only 2.5%
of its
The
$250 increase represents
discretionary income.
increase has a more significant
sees its taxes
Clearly,
the tax
impact on the lifestyle of
the household with less discretionary income.
To the extent that
community, higher
households seek a more homogeneous
property taxes
become a price
into higher income neighborhoods.
who have
more discretionary
high taxes
of entry
Higher income households
income are less
than lower income households.
sensitive to
Accordingly, by
choosing to provide a greater amount of public services and
charging
income
lower
higher taxes
towns prevent
to finance
entry
income households
those services,
into
who
higher
their neighborhoods
cannot meet
the higher
by
tax
price of entry into the community
Similarly, by imposing
restrictive zoning ordinances,
such as requiring minimum lot or structure sizes for homes,
towns
promote
homogeneity.
relatively less
minimum lot
drives
Even
suburban
expensive, the requirement of
size or constructing a
up the
if
cost of
buying a
land
is
acquiring a
minimum size structure
home and
prevents lower
income buyers from moving into the community.
Thus,
suburban
higher taxes
communities to
other homebuyers.
rates could
and
zoning are
raise
methods used
their price
of entry
by
for
To the
extent this occurs,
higher tax
be correlated
with higher, rather
than lower
housing prices, contrary to
such practices.
expectations in the absence of
Section
of this
II
studies
previous
of
study
the
for the
its
addresses the issue of
observed
and discusses
public
variables selected
regression analysis, while Section
limitations.
of
Section III provides further
the reasoning behind the
IV reports and
the analysis, and discusses some
interprets the results of
of
an overview
between
relationship
services and property values.
discussion of
provides
Section
V
summarizes
the
study,
whether capitalization was actually
policy
some
implications of
the
results observed.
II) LITERATURE REVIEW
The theory upon which most literature regarding
property tax and public service capitalization is based was
first developed by Charles M.
Tiebout in his 1956 article,
"A Pure Theory of Local Public Expenditures" [16].
suggested that
individuals indicate their
Tiebout
preferences for
local public goods by choosing to live in communities which
meet their preferred provisions of local public goods.
Public goods are partly defined
consumed simultaneously by
consumption
subtracts
as goods which can be
individuals and no individual's
from
any
other
consumption (i.e., non-rivalrous consumption).
example is
is
national defense.
a problem
of efficient
At the
which
consumers
indicate
their
The classic
federal level, there
allocation because
market for private goods, there
individual's
unlike the
is not a mechanism through
preferences
for
public
goods.
If there
of public
were such a mechanism,
goods would be
adopted.
Instead,
an optimum amount
provided and an
inefficiencies
appropriate tax
occur
because
the
government attempts to adjust its provision of public goods
to what it perceives to be the desired level of the typical
voter.
To the extent that the desires of the typical voter
(assuming such
desires are properly identified)
vary from
what is socially optimal, the allocation is not efficient.
Tiebout
goods
argued that
(e.g., local
efficient because
consumers
the allocation
police
and fire
communities
which
preferences for local public services.
in part because mobility
far greater than among nations.
who are dissatisfied with
goods to
more
fixed, and
conform
to
their
Such efficiency can
among communities is
It is difficult for people
the national provision of public
pick up and move
not as difficult
public
protection) is
local budgets are relatively
select
be realized
of local
to another country.
to move to another community
But
it is
if they are
dissatisfied with the provision of local public goods.
The
simplest
form
of
the Tiebout
model
made
the
to
the
patterns
are
following assumptions:
1.) Consumers
community
are
where
fully
mobile
and
move
their preference
best met.
2.)
Consumers
have
full
knowledge
of
differences
among revenue and expenditure patterns.
3.)
There is a large number of communities from which
consumers may choose to live.
4.)
Restrictions due to
employment opportunities are
not considered.
5.)
There are
no external economies
between
or diseconomies
communities
from
pattern
of community
public
services
supplied.
6.)
For
every
there is an optimum
is defined
services
community size.
in terms
The optimum
of the number
for which the pre-set
set,
of residents
collection of public goods
can be provided at the lowest average cost.
assumption
Without
introduces scarcity
it,
regardless
communities
of the
into the
could double
This
model.
in
limited availability
size
of some
public goods such as parks or beachfront.
7.)
Communities
attract
below
new
average costs
at
the
the
optimum
residents
in order
size
to
of providing public
optimum
size
try
to
seek
lower
goods.
keep
to
the
Those
population
constant.
Given this set of
consumers who
goods in
assumptions, Tiebout theorized that
are discontent with the
their communities
will move to
satisfy their preference patterns.
to
move, reveals
goods.
Thus, in
provision of public
the consumer's
communities that
Moving, or choosing not
demand for
the long-run, communities are
local public
made up of
homogeneous populations with relatively uniform preferences
for local public
allocation
of
goods.
public
This results in
goods
than
the
a more efficient
allocation
at
a
national
level
because
the
consumers
indicates their
goods
a
in
manner
heterogeneous
aggregate,
population
assuming a
which conform
of
communities
willingness to
which cannot
each community demands
goods
choice
on
be
pay for
national market
level.
by
In
for public
only the number of
to the
public
accomplished
a national
by
a
the
goods,
units of public
preference patterns
for that
community.
The total demand (the sum of the demands of the
individual
communities) more
preferences
of
consumers
closely represents
than
a
central
the true
government's
attempt to determine the typical consumer's preferences.
Tiebout
model.
recognized a
few of
the limitations
First, the costs of moving are a cost of indicating
demand.
To
public
the extent that
goods rises,
between
remaining
the costs of
residents are
in
the
providing local
faced with
community
increased costs (which might
and
of moving,
the less
optimal is
within the community.
relocate
indicate an
The greater the
the allocation
Residents
unwillingness
public goods are forced to
the
be greater than the perceived
public goods
to
the choice
incurring
benefit) or incurring the costs of moving.
costs
of the
to
of
who wish to
pay more
for
remain in the community because
moving costs restrict mobility.
Second,
the assumption
diseconomies ignores
public
goods
the benefit
provided
example,
if
benefits
(except to
Town
of no
A
by
an
has good
the extent
15
external economies
to one community
adjacent
law
of the
community.
enforcement,
that criminals
or
Town
For
B
who might
otherwise have chosen to commit crimes in Town A are driven
to
Town
B
because
enforcement
in
of
Town
a
perception
B).
The
externalities occur suggests that
integrating
the
communities,
provision
rather
than
of
extent
inferior
to
law
which
such
there is some benefit to
of these
public
having them
goods
provided
among
by
each
individual community.
Third, although
the model
assumes there are
a large
number of jurisdictions from which the consumer can choose,
it is clear that there is
ultimately a limit to the number
of communities
which can be formed.
obtain exactly
the amount
his
preferences.
Thus,
found at
national level
or
her
inefficiencies
Each consumer cannot
of public goods
the
which reflects
some
of
the
same
appear to
a
lesser extent in the local public goods model.
Despite these
limitations, Tiebout's model
the point
of reference for exploring
consumers
do pay
provide
a greater
limited,
however,
more
for housing
amount of
to
the
discussion of a relationship
public goods
and a
serves as
the possibility that
in communities
local public
extent that
goods.
there
is
which
It
is
not
a
between a preference for more
price associated with
obtaining them.
The process described is merely one of choosing a community
based upon its provision of public goods, without reference
to
the payments
necessary
payments could be made in the
to obtain
those goods.
Such
form of taxes or in terms of
greater housing prices, but at its basic level, the Tiebout
model does
not raise
this issue.
Accordingly,
we cannot
conclude
directly
from
homebuyers express
the
model
a preference
whether
in
for more public
fact,
goods by
bidding up home prices in towns where more public goods are
provided relative
public
goods.
to prices
The
model
explanation regarding the
in towns which
only
serves
provide fewer
to
provide
an
relatively homogeneous nature of
the preference patterns within a community.
Hamilton
pointing
[4],
out that
communities
without a
was
critical of
the mere
was not
public goods.
He viewed the
zoning restrictions, as the
an
urban
area
jurisdictions.
with
a
to ration the
therefore serve as
model,
choice among
for efficient
allocation
consumption of
property tax, in concert with
pricing mechanism when used in
large
He argued further
city, property taxes do not
Tiebout
availability of
sufficient
pricing mechanism
the
number
of
independent
[5], that in the central
act as a pricing mechanism and
an excise tax which
increases the cost
of central city housing relative to suburban housing.
Hamilton argued that the Tiebout model characterized a
situation where the poor would follow the rich into suburbs
as
"free-riders," hoping
base of
the wealthier communities.
would continue
to form new
would continue
to follow.
in low tax
in these
types
of
to benefit
from the
The
While increased
eliminating land
users
including
the poor
housing prices
entry, vacant land
communities would eventually be
property
wealthy, in turn,
communities to which
rate towns would discourage
larger tax
developed by all
low-income
price differentials due to
housing,
the favorable
tax base.
Restrictive zoning prevents this,
incorporated
allowing
it into
each
his
version of
community
to
the Tiebout
enact a
residents to consume a minimum
and Hamilton
law
model,
requiring
amount of housing.
all
He also
introduced a proportional property tax to the model.
In such a model, Hamilton hypothesized that in a state
of
long-run equilibrium,
households would
community whose minimum housing
to
the household's
household
in a
requirement is less, it can
to
a
town
with
community
will
long-run,
there
more
have a
are
households consuming
the
requirement was just equal
desired housing
were located
reside in
consumption.
community where
If
the
the minimum
increase its utility by moving
restrictive
zoning
larger
base.
tax
homogeneous
their utility
because
Thus,
communities
that
in
the
with
all
maximizing combination
of housing and public goods.
Under
these
conditions,
property taxes serve purely as
and do not
according
to
Hamilton,
a price for public services
affect the price of housing.
The property tax
acts almost as efficiently as a head tax because the system
of
restrictive zoning
communities
goods.
ordinances
with similar
Thus, the
results in
demands for
homogeneous
housing and
public
cost of goods can be
spread evenly over
households by charging a
property tax which
is almost uniform across the community.
Each community has
the number of
a different tax based upon its
housing consumption.
demand for public goods and
The tax is less efficient than a head
tax only because the model calls for sorting by preferences
for both housing consumption
and public goods consumption.
If a head
tax were imposed, sorting would
regard to
the demand for
occur only with
public goods, leading to
a more
efficient benefits tax.
Hamilton
goes on
occurs only in
to
point
out that
capitalization
a state of disequilibrium where
there is a
scarcity of some type of
desired community.
land uses are shifted to
activities which earn an economic
rent (i.e.,
and
a rent in
overhead)
attributes.
property
A
values
excess of market returns
by
providing
positive
or
becomes
the
taxes
are in
negative
dependent
short
supply,
capitalized into higher prices.
short
supply, communities
of profit
desired
community
relationship
upon
communities which are in short supply.
lower
In that case,
the
with
types
of
If communities with
lower taxes
will
be
If public services are in
which
provide relatively
more
public services
will experience a capitalization
of those
services
higher
long-run
into
equilibrium,
accordance
however,
with
preferences
the
housing
results
housing
in
prices.
sorting
of
consumption
property taxes
In
communities
and
public
in
goods
representing
the
price of public services and capitalization does not occur.
Hamilton's conclusion from an empirical study [5], was
that the Tiebout model operates
where
there
choose so
public
are enough
that property taxes
goods.
limited and
school
In
the
the property
only at the suburban level
districts
are viewed as the
central city,
tax is viewed
19
from which
choices
as an
to
price of
are
more
excise tax
which
increases
the
cost
of
housing
and
decreases
consumption relative to the suburbs.
This
conclusion
Ihlanfeldt
[7],
was
whose
further
1984
Metropolitan Statistical Areas
in central
city housing
tax
consumption
agreement
while
payment
of housing
they
30
associated
tax increase,
with
for local
excise
a
greater
Ihlanfeldt stated
hypothesis that
represent an
Standard
(SMSAs) indicated a decline
services.
as payment
of
by
was either a neutral effect or
was
with Hamilton's
are viewed
study
consumption with a
while in the suburbs, there
a higher
substantiated
property taxes
services in
tax
his
the suburbs
on housing
in
the
central city.
The
indication
taxes and
of
a positive
property values in
Ihlanfeldt
and
explanation.
Hamilton
Those
relationship
the suburbs observed
studies
communities
has
a
with
relationship between
taxes and property values
perceived
value of
a present
which exceeded the
between
benefits from
present value of the
a
in the
plausible
positive
could have
public goods
taxes required to
receive those public goods.
Hamilton's point would be that
such an excess of benefits
over costs was not perceived in
the central city.
Barriers to mobility such as restrictive
zoning and the limited
choices of jurisdictions within the
central city
serve to prevent central
exercising a
jurisdictional choice in accordance
Tiebout
model.
Faced
with those
city consumers from
with the
barriers, central
city
consumers who view the tax as too expensive relative to the
20
benefits
provided reflect
that
view
by consuming
fewer
housing services rather than moving.
In addition to the practices of restrictive zoning and
higher
taxes, another
towns concerns
public good.
form
the concept of
which
serves to
acquisition can
good.
be
However,
space involves
the
acquisition
is
can convince
land, the
expense
of
residence,
viewed as
more
the
extent
procurement of
of others from
accurately
a
such open
enjoying it,
described
as
a
Further,
if the town
or Federal government
to purchase
townspeople
might not
of land
To the
enjoyment of
a public good.
taxpayers
Such
benefit of more open space,
since the
the state
the cost
for development.
the exclusion
collective good than
the
than a
space within its community.
increase taxes and
remains available
public
suburban
a collective rather
that the townspeople enjoy the
the
used by
A town can vote to acquire tracts of land for
the preservation of open
an action
of barrier
who,
ever
enjoy the
due
to
open
space at
their
benefit from
the
location
the open
of
space.
Groups of homeowners who suddenly become very excited about
establishing
motive
of
"conservation
increasing
the
areas"
price
often
of
have
entry
the
into
true
their
communities.
The view of
value
a perception of a surplus
of benefits
present
services
value
from
of the
was advanced
public services
taxes
required
by Oates
[11].
in the present
relative to
to pay
In
for
the
those
describing the
Tiebout model, Oates stated that the property tax liability
represents the price of consuming local public services.
consumer concerned
the community
surplus in
with maximizing utility would
in which
he or
she perceived
the present value
public goods
relative to the
tax payments
required to
of the future
A
seek out
the greatest
benefits from
present value of
the future
receive those goods.
Thus, all
else equal (including tax rates), property values should be
higher
in
the
community providing
the
more
attractive
package of public goods.
To test
towns in
level
this hypothesis, Oates gathered
northeastern New
of
output of
expenditures per
the
use
of
public
pupil.
this
Jersey.
services,
variable
public services
spending might
not accurately
of
primary
and secondary
his proxy
educational
for the
Oates used
He recognized the
noneducational
quality
As
data from 53
because
and because
school
limitations of
it
neglected
variations in
reflect differences
services.
education
in the
Nonetheless,
represented the
since
largest
single item in most public budgets and was of importance to
families with
proxy for
children, he felt
it was a
reasonably good
exploring the potential capitalization
of local
public services.
Other variables utilized in the Oates model were:
1.) Linear distance of the municipality from midtown
Manhattan as a measure of proximity to the major
employment center
2.) Median number of rooms per dwelling as a measure
of size.
3.)
Percentage of homes in the community built since
1950
as a
measure of
of the
the age
housing
stock.
that this
income; Oates reasoned
4.) Median family
such as
reasonable proxy for intangibles
was a
attractiveness of the
would
select
tax rate, defined in
all of
presumably
families
wealthier
stated that
He
the house.
beauty of
charm or
neighborhood, or physical
higher quality residences.
5.)
Effective property
nominal tax rate times the
these studies as the
assessment ratio used in the community.
of families
6.) Percentage
the study
that
values
was
with poorer
weighted
downward
median
to explain
and
in
who tend
to
dwellings
families
homeowners would
family income of
rent, median
by
was
reasoning here
trying
owner-occupied
of
communities
be
The
under $3000.
incomes
with
the community
in
a
large
renting
population.
After
variables,
regressing median
Oates found
taxes and
that property
values were
and property
values
concluded
on these
negatively related and expenditures
values were
the
home values
of
the
that
unaccompanied
an
by an
positively related.
coefficients
increase
increase
in
in
in
his
property
seven
property
per pupil
Based upon
equation,
tax
expenditures per
he
rates
pupil
would cause a reduction in
rate
increase
were
property values.
accompanied
by
However, if a
an
increase
in
expenditures per pupil, the expenditure increase's positive
effect
might
offset, or
more
effect of a higher tax rate.
a validation of
in
offset the
more to live in a
it indicated that
community which either
relatively high-quality output of
relation to
the taxes
negative
This was seen as somewhat of
the Tiebout model since
people would pay
provides a
than
charged, or
public goods
the same
level of
public goods at lower tax rates.
Oates discussed the problem of using expenditures as a
measure
of the
output of
local public
goods, a
problem
which exists in most of the studies conducted in this area.
He also
noted that the
utilized
in
this
represented points
strictly true.
Hamilton
study) assumed
observations
of equilibrium, which was
probably not
In fact,
[4], concluded
it is
that
(as are
the
directly attributable
point of
use of cross-section data
interesting to
the results
to his
note that
Oates obtained
were
observations occurring
at a
disequilibrium, and that
at a point
of long-run
equilibrium, such capitalization would not have occurred.
In response to a critique
[13],
Oates [12],
including a
all
This
than
local public
additional variable was
property values,
hypothesis.
version of
the regression
variable for municipal spending
functions other
service.
with
ran another
of his model by Pollakowski
as was
Also, whereas
schools and
debt
positively related
expected under
Oates had
per capita on
the Tiebout
concluded from
his
first
model
that
capitalized
rate
property
into
differences
were
this
values,
partially
model
revised
roughly
indicated
expenditures
public
all
including
tax
complete capitalization of tax rate differences.
communities near
thirty-nine
as
a
interpreted their
separate
The data further
values.
They
strong positive
and
expenditures
school
student
per
variable.
independent
results as indicating a
between
relationship
4)
and
Environment;
school expenditures
Annual
Transportation.
remained
Community
3)
subdividing
Public Health and
Persons and Property; 2)
Services;
Social
Columbus, Ohio,
education into four categories:
public services other than
1) Security of
similar study of
Ingene [8], conducted a
Kohlepp and
property
suggested that spending on other
services did not affect property values.
While the
and Ingene
did find that
services and
theorized
rather
coefficients were not
the signs for both
public health variables were
that
than
such
outputs
questioning the
for services.
a high
relationship
of
local
health and
would
negative.
public
level of
services,
security.
and property
again
as a proxy
of a crime problem rather
Similarly,
for
decreased
the negative
public health
values could
social service problems in
in
to
relationship for public safety
between expenditures
probably result
They
inputs
validity of using expenditures
The negative
social services
the security
expenditures represented
expenditures might be indicative
than
significant, Kohlepp
and
reflect public
the community which
demand for
housing.
However, one must keep in mind that these coefficients were
not statistically significant in their study.
The model
also uses several
developed for this study
in the sample
of the public budgets
individual components
towns to examine whether those particular expenditures have
a significant
on
effect
than
Rather
values.
property
dividing all expenditures into one of four categories, this
at expenditures
looks specifically
study
for
per capita
service and all budget items
police, fire, education, debt
other than those four.
Two other studies addressed the metropolitan nature of
the
Tiebout process,
that in
commenting
nonmetropolitan
areas, capitalization of property taxes and public services
was
not as
They theorized that in less urbanized
more local, such that
areas, employment opportunities were
interjurisdictional mobility was limited.
was more
of housing
because
the supply
distance
were
value
elastic than
of undeveloped
of employment
fewer constraints
industry and
of
studied
in North Carolina, excluding the
one-hundred and six towns
nine largest cities.
Pasour [6],
Hyman and
significant.
in the
the ratio of the
residential real
urban Northeast
land within
opportunities
upon entry
Also, the supply
was greater,
into the
was
there
construction
value of land to
estate
commuting
lower.
the total
In
North
Carolina in particular, most school funding was provided by
the
state,
so there
was
relatively
little variance
in
property tax rates across communities.
Given these considerations,
26
Hyman and Pasour expected
of public expenditure and property
to find little evidence
in
were
with
line
the
services,
dollars, on
capita basis,
a per
for local
taxes
local
of annual
amount
The
was negative,
Their proxy
statistically significant.
public
North
expectations.
their
effective property tax rate
coefficient for
but not
of
areas
urbanized
Using an Oates-type model, they obtained results
Carolina.
which
less
in
capitalization
tax
and mildly
was positive
Hyman
significant, but its magnitude (.21) was very small.
and Pasour did not
did their
nor
aggregate
local
tax
examine any specific local expenditure,
from
assumes
local
expenditures in
examine public
study
One
aggregate.
in
to
grants
that state
and
collections
equivalent
are roughly
expenditures
that
utilized
proxy
the
the
to
local
governments are roughly equivalent across communities.
Carlson [10],
McMillan and
in
Wisconsin, theorizing
North
Carolina
sensitive
property
could
caused
rates
in
two-and-one-half times those in
small
cities there
Pasour's
similar results
of
would
conclusions.
property tax
be
Wisconsin
rates in
less
be
there.
were
Since
nearly
North Carolina, a study of
test
a good
McMillan and
capitalization was
of Hyman
Carlson
and also concluded that
public service
to
demand
among communities
to differences
tax
that low
have
similar study
conducted a
and
experienced
the Tiebout model
less applicable
to
nonmetroplitan areas.
Some
of
the
reviewed here are:
basic
conclusions
of
the
literature
1) The Tiebout model
hypothesizes that consumers shop
among communities and locate in the ones which best
of local
preferences for the provision
meet their
public goods.
2) In
long-run equilibrium
and property
with zoning
restrictions
taxes, capitalization does
not occur
because taxes serve as the direct pricing mechanism
for public services
is more evident in
3) Such shopping among communities
the suburbs relative to the central city.
Property
taxes are viewed in the suburbs as a cost of public
services but in the central city as an excise tax.
4) Property tax and
public expenditure capitalization
is less evident in nonmetropolitan areas.
5) If
capitalization does
more with
associated
appears to
it
occur,
education expenditures
be
than
with expenditures on other public services.
considered in
The towns
six
miles from
to twenty-one
suburban areas of a
would expect
Kohlepp and
of
property
Tiebout hypothesis in
major metropolitan area.
results
similar to
those
Ingene, indicating a degree
tax
rate
differences
located from
should provide
Boston, and
the operation of the
evidence as to
we
this study are
and
Accordingly,
of Oates
and
of capitalization
differences
education expenditures, if not all public expenditures.
in
III) THE MODEL
To study the relationship between local public
linear regression model is
estimates by
based upon
data
upon
relies
describing
used.
describing the median
census data
area
property values,
and residential
expenditures
in an
value of housing
the homeowners,
&
this study
Tradesman
[1],
The
data
1989.
sold during
actually
homes
Rather than relying upon
by Banker
supplied
a multiple
county Registry of Deeds for
combines information from the
each town describing the
actual sales prices and financing
terms of homes sold with
the records of the local Property
detailing the
Assessors' offices
This approach should provide
homes sold.
picture
how
of
a more accurate
with
homes
prices
market
the
of the
physical aspects
varying
characteristics than estimates of value could provide.
Ten towns in the Greater Boston area were selected for
stock, the
from
view
order to
In
study.
study looks at
1800 to
housing
sales of homes ranging
in size
square feet.
2200
expect homes in this size
terms of the number of
the model
fairly homogeneous
a
attempts to
prospective homebuyer
general, one
In
would
range to be fairly consistent in
bedrooms and baths provided.
simulate the
situation faced
choosing between
Thus,
by a
reasonably similar
homes in two or more towns which provide different packages
of local public goods.
The dependent
the sale price
variable in the regression
of housing.
A total of 336
equation is
sales of homes
ranging in size from 1800 to 2200 square feet was observed,
excluding a
true,
"arm's length"
sales prices
those cases,
In
transactions.
to be
not appear
which did
few sales
after
the
others and the
were substantially lower than
buyer and seller often had the same last name.
this is
Since
property values
at actual
looks
home sales
to explain
and attempts
the
independent variables,
a number of
subtract from the
which add to or
including expenditures,
between
the model
public expenditures,
and local
terms of
variation in
the relationship
study of
a
sales price (value) of the home.
categories:
Fiscal
1)
the
located; and 3)
the
of
Physical aspects
variables in
three
fall into
variables
independent
The
towns in
general
2)
homes sold;
the homes
which
were
Locational characteristics associated with
the towns.
The five physical aspect variables included age of the
home at the time of sale, square feet of living area in the
home, lot size
the equation, these variables are
In
the number of baths.
shown as AGE, SQ. FT.,
LOT, BDRMS and BTHS, respectively.
The expected sign for AGE
that people
for an
premium
are willing to pay
older house
updating.
range comprise
be in
a very
portion of
30
need of
be willing
old house,
homes in the thirty
a larger
It is assumed
more for a new
buyers might
charm of
expectation is that
is negative.
which might
While some
for the
of bedrooms and
in square feet, the number
house than
repair or
to pay
a
the general
to forty-year old
the stock
than homes
modernized.
been
Such homes are not expected to command much of
and
systems
electrical
and
heating
of
modernization
that
extent
the
to
especially
premium,"
a "charm
have
which
century
the
of
turn
the
at
built
replacement of the roof is required.
expect larger homes to sell for a higher price.
the
are
also
are willing to
the assumption that buyers
positive, under
Similarly,
and BTHS
BDRMS,
LOT,
signs for
expected
One would
FT. is positive.
The expected sign for SQ.
pay more for more land, bedrooms and bathrooms.
was
fiscal data
The
Massachusetts
by the
provided
Those
Municipal Assistance Bureau.
Department of Revenue,
variables include the residential property tax rate (TXRT),
expenditures
police
per capita (DEBT),
debt service
expenditures per
public
protection
(FIRE), education expenditures per
expenditures per capita
capita (ED/CAP),
fire
(POL),
capita
per
capita
and all
fire
than police,
other
protection, education and debt service (OTH).
The expected
with
theory
the
sign for TXRT is
of
negative in accordance
tax capitalization.
factors are held constant,
If
all
other
homebuyers would be expected to
reduce the price they would be willing to pay for a home if
faced with a higher property tax rate.
of real property taxation
An aspect
is worth noting.
portion
of
the
in Massachusetts
Massachusetts law allows towns to shift a
residential
property
commercial and industrial properties.
in individual towns by a vote
tax
burden
to
This is accomplished
of the local town council to
at up to 50% more
tax commercial and industrial properties
a decrease in
offset by
increase is
of taxes
the amount
and those classified as
levied upon residential properties
suppose the total assessed value
For example,
open space.
The
properties.
on those
be levied
would normally
than
of all properties in a town is $2.5 billion, and 75% of the
total
classified
properties
of
comprised
is
value
total value is
space while 25% of the
residential or open
as
from those classified as commercial or industrial.
Suppose
of shifting, the tax
rate in
in the absence
further that
in property tax revenues.
generating $25 million
are taxed at up to 150%
industrial properties so that they
industrial properties
(1.5%),
to $15
and increases
tax
the
increases
This
shifting.
in
have been
would
rate
the
what
absence
the
property value
those
revenue from
properties to $9.375 million ($625 million times 1.5%).
balance
of
residential
open
and
accomplished at a
properties.
burden
on
properties.
An
must
This
of
owners
owner of
paid $2000 in property
shifting is
residential
a $200,000
can
be
(0.8%) on such
tax rate of $8 per $1000
of the
from
raised
be
properties.
space
The result
the
million
$15.625
only
In
$25 million, a
property tax revenues at
order to maintain
of
and
commercial
on
per $1000 in
total tax
the
The law
to commercial and
to shift the tax burden
allows the town
of
property value (1.0%),
be $10 per $1000 of
the town would
and
home who
a lower
open
tax
space
would have
taxes without shifting instead pays
$1600, a savings of $400.
to implement shifting is the
A factor in the decision
percentage of
has a
If the town
industrial properties.
commercial and
comprised of
value which is
total assessed
very high percentage of residential property, there is very
little to
150% of
taxed at
Even when
shifting.
gain by
what the tax rate might have been without shifting, a small
of
amount
and
commercial
cannot
properties
industrial
generate enough revenue to provide significant property tax
relief to a homeowners in a predominantly residential town.
a
is
there
when
However,
base
large
relatively
of
shifting can be very
commercial and industrial properties,
beneficial to homeowners.
has a
which
large
significant
derive
tax
burden
is
by
viewed
the
from
opportunities
If the shifting of
businesses located on those properties.
the
might
industrial base
commercial and
employment
A town
to consider.
additional tradeoffs
There are
those
as
businesses
costs relative
significant increase
in operating
might be experienced
in a nearby community
a
to what
which can draw
upon an essentially equivalent labor force, the firms might
relocate.
However,
residential character
does
not
towns
which
desire
to
maintain
a
might resort to shifting
even if it
order to
discourage
generate much
revenue
in
commercial and industrial development in the town.
A potential homebuyer will consider more than just the
tax effect
of the presence or
commercial or
potential
absence of a large
industrial property users.
negative
externalities
base of
Presumably, the
associated
with
the
presence
of factories
values.
Thus,
live in a
town with a more
order to
If such
dampen
would
this
occurs,
process
have
due to shifting in a town
industrial base.
commercial or
decision-making
incur
"residential character" rather
than to benefit from lower taxes
a large
does not
make shifting worthwhile in
a base to
property
to
willing
town which
in a
enough of
with
to decrease
might be
homebuyer
a
higher taxes
potentially
serve
would
a
the
property tax rate which is
negative effect of an increased
otherwise anticipated.
POL.
Based
and Ingene study,
upon the Kohlepp
expect a negative sign and
the
police budget
However, one could
is
associated with
predict the sign
difficult to
It is
one would
hypothesize that an increase in
a crime
of
an indicator
problem.
large per capita
make an argument that
expenditures for police protection indicate a commitment to
therefore lead to increases in
crime prevention and should
values.
property
again
This
an input to public
expenditures, which are
measure
of
the
and the
of
quality
regarding the number of
issue of
raises the
the
using
services, as a
services.
Statistics
crimes reported per 1000 residents
clearance rate (percentage of
which at least one suspect
reported crimes for
was arrested) would be a better
Unfortunately, the reporting of such statistics
indicator.
is voluntary in
Massachusetts and one of the
towns in the
sample does not report.
whether FIRE should have a
Similarly, it is not clear
negative
or
positive
sign.
Do
large
expenditures
per
Some towns have volunteer
the relationship, such as wages?
security associated
is greater
that there
If one
the town.
contracts with
unions negotiate
argues
full-time firefighters
while others have
fire departments
whose
factor affecting
Might there be another
fire prevention?
commitment to
or a
with fires
a problem
capita indicate
with a
larger expenditure per capita
full-time department, than a
should be positively related with housing values.
upon
Based
is
(ED/PUP)
per
expenditures
Magazine [ 14]).
on
should be
pay more for
Per pupil
greater expenditures.
for comparison
Boston
per pupil
quality, people
of school
an indicator
willing to
better variable
by
supplied
expenditures per capita or
If
education
regarding
(Data
were
pupil
education are
expenditures per
and education
positive.
the
reviewed,
literature
the
for ED/CAP
expected signs
pupil
of
most
housing in
towns with
expenditure is probably a
less highly
because it is
correlated with INC/CAP and SAT than is ED/CAP.
signs for
The
predict.
amount
greater
bonds are
expected
debt service
future tax
per
burden
fully guaranteed
sign
in
district) and
residents
will
to the
extent that
would
view
are utilized
that
be
a
municipal
The
negative.
bonds are backed by a separate
a parking authority or
user fees
risking
government.
by the local
to
with a greater
would be
capita
that circumstance
However, to the extent that
authority (such as
are difficult
OTH
it seems that towns
Intuitively,
of
DEBT and
both
particular
water and sewer
to cover
service
the debt,
as
being
between
debt
is not as
negative as
be as strongly
should not
It
the
values in this circumstance
service and housing
clear.
adding to
relationship
The
burden.
tax
potential
not
users and
the
by
paid for
directly
in the
former case, but should only be positive to the extent that
minority of
a
utilized by
being
residents who
the
fees.
supporting it through the user
bonds as
by the
good financed
the public
residents view
are
If a majority of the
town's residents use the public good and pay the user fees,
a benefits tax and should not
the user fees are serving as
be capitalized into housing values.
spending included
Categories of
include
health
and welfare,
and culture
extent
these public
goods
(though
welfare
are viewed
However, Kohlepp
expenditures
that such
and
sign
in
spending are
equation
the
categories.
recreation and
effect
dependent
of the
general government
and health
and
health and
Since several different
variable, its
the
upon
have a
culture and
strong positive
welfare expenditures
36
relative
various expenditure
example, if expenditures for
For
They
in the negative
included within this
negative effects
positive and
health and
expenditures indicated
is
the
for OTH should
values.
property
relationship with property values.
kinds of
To the
and Ingene found a negative
in a community, resulting
social problems
works,
adding to
as
relationship between
not significant)
hypothesized
and recreation.
in a community, the sign
"quality of life"
be positive.
public
fixed costs,
government,
general
OTH variable
in the
have a
mild
negative
effect,
other
the
variable
will
be
Conversely, if the negative effect of health and
positive.
welfare
for
sign
the
outweighs
expenditures
components of
variable, its
the OTH
effects
of
sign will
be
the positive
negative.
The
locational
characteristics
of the
a
few
They include
the
are indicators
variables
sample
towns.
of
average combined SAT scores for high school students in the
town
(SAT)
[14],
(INC/CAP ) [17],
the
town's
the distance
Boston (DIST) [17], and the
assessed value
(%
space
income
in miles
(also
capita
from the
town to
percentage of the town's total
which is classified as
RES/OP)
per
residential or open
by
provided
the
Massachusetts
Department of Revenue, Municipal Assistance Bureau).
The use of
average combined SAT scores
to measure school quality.
this.
First,
variables
in the
correlated
be
There are several problems with
correlation matrix
equation,
with both
ED/CAP were
might
when a
SAT was
INC/CAP and
of
a
proxy for
was run
found
income
for the
to be
ED/CAP and
highly correlated with each
more
is an attempt
INC/CAP and
other.
per
highly
Thus, SAT
capita
and
education expenditures per capita
than for school quality.
Second,
between
there
capita in
is a
correlation
a town and
the income
the percentage of students
per
who take
the exam; the greater the per capita income, the higher the
percentage of
the per
students taking
capita income
percentage
of
all
is in
students
the exam.
a town,
whose
Thus,
the lower
the smaller
performance
is the
can
be
measured by the SAT, because a relatively larger percentage
public schools,
attend the
these students
system.
school
of students
in these school
an
test, ranging
Thus, a large number
54% to a high of 92%.
from a low of
towns sampled,
took the
the students
SAT by
the public
the quality of
the ten
for
Finally,
on the
so performance
is unrelated to
76.8% of
average of
towns do not
13.8% of the students in these
an average of
Third,
not sit for the SAT.
of students in those towns do
the exam
systems do not take
used in this model as a measure of school quality.
Despite these shortcomings, it does seem reasonable to
presume
considering the
that parents
would look for some
purchase of
a home
quantifiable measure of school quality
and published reports of SAT scores might be influential in
the
homebuying
decision.
If
potential for their children to
the
that
score higher on the SAT is
particular town,
in a
enhanced
by attending
the schools
they are
likely to be
willing to pay
that town.
feel
parents
home in
more for a
Thus, the expected sign for SAT is positive.
The expected sign for INC/CAP is positive.
Oates used
median household income in his model as an indicator of the
stock, hypothesizing that wealthier
quality of the housing
buyers would demand higher
more
quality indicators
quality homes.
than the
This model uses
Oates model,
upon the
theory that as
income rises, demand
services
increases,
variable
included.
Household
a
income is
for
a more
income
but based
for housing
is
still
desirable measure,
but most current available data for household income is for
38
towns in
and two of the
populations of 25,000
areas with
the sample have populations below 25,000.
land markets is that
theory of urban
as
willing
costs.
commuting
are
costs
commuting
decreased
Thus,
with increased
in accordance
for housing
to bid
to their
amount they are
and will decrease the
place of employment
increases.
live in close proximity
pay more to
People will
land values decrease
employment center
the major
distance from
The basic
is not clear.
sign for DIST
The expected
capitalized into land prices.
households with
However,
higher
incomes who
demand
more housing are expected to move further out from the city
and
of high
households at
income
costs
commuting costs.
of
commuting
are
to benefit
households
the
a tradeoff
point
land costs just offsets the
where the benefit of decreased
increased
exchange for
result of this process is a
The
ability to own more land.
location
costs in
commuting
accept greater
points
At
too
the
for
higher-income
ability to
purchase less
great
from the
further out,
expensive land.
This concept
becomes complicated in
metropolitan areas such as Boston.
the
largest
significant
employment
nodes
Routes 128 and 495.
of
center
employment
Many of
factor in
While the Boston CBD is
in the
there
area,
surrounding
Boston
are
on
the residents of the towns in
this sample could be employed in
commute to another
highly developed
one town on a beltway and
such that proximity to Boston
the household's location decision.
is not a
Thus, it is
difficult to predict the sign for the DIST variable.
The predicted sign
not clear due
for %RES/OP is also
to the factors discussed above with regard to tax shifting.
If
of
avoidance
potentially
higher
greater
tax
is
one would
taxes,
between prices
relationship
potentially
externalities
more
expect
and %RES/OP.
burden is
more
than
important
a
positive
If avoiding
a
important,
the
for
the
expected sign would be negative.
Table
variables in
next page.
1
summarizes
the
expected
the regression equation
signs
and is shown
on the
TABLE 1 - SUMMARY OF EXPECTED SIGNS
EXPECTED SIGN
VARIABLE
AGE
-
SQ.FT.
LOT
BDRMS
BTHS
TXRT
POL
FIRE
-
ED/CAP
?7
ED/PUP
+
DEBT
OTH
+
SAT
?7
INC/CAP
DIST
?7
% RES/OP
IV) RESULTS, INTERPRETATION AND DISCUSSION
The results
highest
R2
coefficients
with
combining the
of the regression equation
the
greatest
and relatively
number
of
little correlation
significant
among the
coefficients are shown in Table 2 on the next page:
TABLE 2 -
REGRESSION RESULTS
Value
Coefficient
t-statistic
-154,050.000
3.036
-295.034
2.955
SQ.FT.
-3.681
0.840
LOT
+0.385
2.897
-523.957
0.134
BTHS
+25,249.040
4.478
TXRT
+46,420.810
7.501
POL
+1,534.926
2.667
FIRE
-1,357.020
3.709
+45.899
5.670
DIST
-3,111.720
3.275
DEBT
-1,446.950
4.817
-397.101
9.029
CONSTANT
AGE
BDRMS
ED/PUPIL
OTH
*
R2 = 0.498
*
-
Denotes
coefficient
significant
not
the
at
95%
confidence level
The
regression
expectations, but
results
not all.
2
was the value of R2.
were
in
One of the
line
with
some
overall surprises
In most of the literature, the values
for R2 were in the 70% to 90% range while the best obtained
with
this data
was
an equation
which contained
several
only upon
represent finer
size may
constrained physical
The
feet.
One
2200 square
1800 to
in size from
homes ranging
51.8%.
of the study
is the focus
possible explanation
sales of
an R2 of
variables and had
highly correlated
pricing distinctions than can be explained by the variables
quality of
construction, architectural
and
neighborhood
other
such as
size range, factors
Within the
equation.
in the
style, landscaping
significant
have
could
effects
influence on prices.
study
most
used more
of
Oates,
physical variable
and
then
of
the use
excludes
income
tax
and
and
rate
This study uses
equation
in the
above
significantly
less
somewhat
correlated with expenditure per
pupil.
The elimination of
correlated variable could explain
this highly
family
to be highly correlated with
because income data was found
price
utilized median
account for housing quality,
several physical variables to
and
the
dwelling as his
proxy for housing quality.
income as his
sold than
example, used
for
of rooms per owner-occupied
median number
only
regarding homes
physical data
the literature.
used, this
the variables
difference in
as a
As far
some of the
reduction in the value of the R2
All
of
the
variables
in
equation
the
were
statistically significant at the 95% confidence level, with
the exception
these
of SQ.FT.
two variables
definition of homes
sample are 1800
is
and BDRMS. The
insignificance of
also attributable
to be sampled.
When all
to 2200 square feet, it
to the
narrow
homes in the
is not surprising
that the significance of square footage is reduced relative
the
bedroom could
an additional
sampled,
size range
Also, within
broader range of sizes.
sample with a
to a
be
throughout the house and could
indicative of smaller rooms
therefore have a negative effect on price.
The regression results demonstrate
regard
with
especially
capitalization,
expenditure
a degree of public
to
police expenditures per capita and educational expenditures
all
for FIRE, DEBT, and OTH are
However, the signs
per pupil.
Further,
negative.
does not
there
seem
to
be
a
demonstration of tax capitalization since the sign for TXRT
is positive.
An
some
provides
the
of
examination
correlation
A
explanation.
the
of
variables
matrix
correlation
[9]
indicates that FIRE is highly negatively correlated (-.577)
That is, expenditures per
(-.514).
with OTH and with TXRT
are higher.
tax rates and other expenditures
are highly
positively correlated
The correlation
of some
and TXRT
was found
(.504).
INC/CAP
(.581).
towns,
be lower when
protection services tend to
capita for fire
other (.665).
other variables was
also tested,
highly correlated
with INC/CAP
to be
is
with each
TXRT and OTH
also highly
correlated
with
price
This leads to the hypothesis that in higher income
prices and
tax rates
tend
to be
higher, as
are
expenditures for public goods other than education, police,
fire,
and
homeowners
debt
pay
service.
higher
In
these
taxes and
greater share of those revenues
towns,
allocate
a
wealthier
relatively
to expenditures in the OTH
Conversely, in lower income towns,
category than to FIRE.
lower, and so are expenditures in
prices and tax rates are
Less
the OTH category.
If this
tax revenue to
relatively greater share of
and allocate a
FIRE.
wealthy homeowners pay lower taxes
would help explain
hypothesis is valid, it
why the sign for TXRT is positive and FIRE is negative.
an
in
income
higher
towns, associating
their
as
are serving
variables
extent, these
To
a proxy
for
prices
with
higher taxes and lower prices with greater expenditures for
Although the
fire protection.
is negative,
sign for OTH
and its effect could be masked
its magnitude is not great,
by the positive correlation with TXRT.
A further
possible explanation for the
high positive
relationship between TXRT and price lies in the correlation
of total
the percentage
between
which is
assessed value
classified as residential or open space (%RES/OP) and TXRT.
The
.742,
indicating
residential
have
and %RES/OP
between TXRT
correlation coefficient
that
towns
which
higher
tax
rates.
are
is
predominantly
This
makes
sense
considering the ability of towns to shift the tax burden to
commercial and industrial property.
very little commercial and
to
gain
by
shifting
Those towns which have
industrial property have little
while
those
with
a
large
commercial/industrial base can derive a significant benefit
in terms of reduced
one would
expect tax rates
relatively
However,
residential property tax rates.
on residential property
greater
in
predominantly
there can
be
negative externalities
45
residential
Thus,
to be
towns.
associated
in a town
to live
greater taxes
the
avoid
character
and
contribute
to a
incur
prefer to
would
homeowners
that some
such
base,
larger commercial/industrial
with a
in towns
with living
more residential
with a
would
This
externalities.
and
between price
positive relationship
an indicator of the residential
TXRT, with TXRT serving as
nature of the town.
which lends greater credence
(.487),
and per capita income
buyers bid up
Assuming higher income
hypothesis.
to this
between %RES/OP
also a positive correlation
There is
the prices in towns with more residential property, seeking
commercial/industrial
taxes.
In
it
base,
not
is
higher taxes
a sense, the
larger
a
to
unreasonable
to higher
are less sensitive
such homebuyers
assume that
with
associated
externalities
avoid
to
as a
can be viewed
cost of avoiding externalities just as they are viewed as a
cost of receiving public goods.
sign for DEBT indicates
The negative
apparently
potential
risk
indicator
of
of
positive correlation
an
indicator that
expenditures,
cruisers,
supported
than
services.
The
between DEBT and POL
used to
debt is
including
annual
radio equipment,
etc.
capita as
rather
taxes
increased
user-fee
service per
debt
view increased
that homebuyers
an
strong
(.838) could be
finance some
replacement
The
as
a
of
capital
police
correlation between
DEBT and TXRT is extremely low (.000322), which might be an
indication that the towns in
this sample do not incur much
debt.
46
The negative
to distance
these
from Boston
suburban
housing
sign for DIST indicates
in determining housing
towns.
values
The
decrease
coefficient
approximately
additional mile away from Boston.
of
employment centers
some importance
in
values in
estimates
$3,100
that
for
each
Again, due to the number
the area,
it
is difficult
to
determine what factors contribute to this outcome.
With regard to the physical
results
also point
bathroom.
According
bathroom adds
since
the importance
to
the
over $25,000
the size
makes sense
of the
that the
greater importance.
the
out
fixtures
factors in the model, the
in value
addition of an
Also, since the
exceeds the cost of adding
additional
one
additional
equation,
to a
homes sampled
and plumbing
of an
house.
Again,
was restricted,
amenity would
it
be of
cost of adding all of
required
for
a bathroom
far
a bedroom, it is not surprising
that the additional bathroom
has a more significant impact
on the overall value of the house.
While AGE
and LOT
were statistically
significant in
determining value, the magnitude of the coefficients was so
small that the overall effect on price was minimal.
Overall,
the
housing value as
effects of
most
significant
variables
indicated by the model
TXRT and
BTHS. As
reasons to believe that the
affecting
were the positive
discussed above,
there are
high positive value of TXRT is
associated with some other factors such as the avoidance of
negative externalities and a positive income elasticity for
housing
demand.
These
influences
could
have served
to
erase the expected
negative effect of higher
tax rates on
explored the relationship between
local public
price.
V) CONCLUSIONS
This study
expenditures and single-family property values in ten towns
in Massachusetts.
It utilized multiple
to develop a hedonic pricing
constant for
linear regression
model which attempted to hold
several variables thought to
affect the sale
price of homes.
The anticipated
results were a
negative relationship
between prices
and tax
between prices
and public goods expenditures.
that other
rates and a
factors, such as
externalities
associated
development, or
positive relationship
the desire to
with commercial
It appears
avoid negative
and
zoning and taxation practices
industrial
designed to
create more homogeneous communities
with respect to income
caused the relationship between tax
rates and values to be
expressed as
public
positive in
the model.
However,
expenditures were
negatively
related with
education expenditures
This was
Since
in keeping with
the towns
capitalization.
a large
(an average of 45% of
sampled here),
strong
make up
this topic.
portion of
the budgets in
this positive relationship
indicator
of
price,
positively related.
previous studies of
education expenditures
local public budgets
fairly
per pupil were
while some
public
is a
expenditure
suburban areas,
in
that
sorting
in
themselves
between
prices which
taxes and
for
preferences
suburban homebuyers
public goods.
the price of
finding of
explained their
This
with
partly because
property taxes as
viewed real
people
process of
Tiebout
the
accordance
goods operated
public
who concluded
[5] and Ihlanfeldt,
by Hamilton
in studies
to those found
this study are similar
The results of
a positive
relationship
observed in
was not
the
central city.
the suburban versus
study did not address
While this
central city issue, the phenomenon of property tax shifting
in Massachusetts
such a
are
allows for an additional
explanation for
It appears
that homebuyers
positive relationship.
partly motivated
at least
towns with
by a
desire to
locate in
is characterized
a residential character which
by a scarcity of commercial and industrial development.
Massachusetts, such
relatively
towns can
tax
high property
commercial/industrial base
from a
part
provision in
the
of
property
tax
allows towns
burden
to shift
commercial
to
and
to locate
be bid up there in spite of
countering the
tax rates
small
from benefitting
Nonetheless, the desire
tax burden,
as having
because their
prevents them
in such towns causes prices to
relationship between
rates
the law which
industrial properties.
the greater
be characterized
In
expected negative
and property
values.
The
tax rates and
high correlation
between income per capita,
prices indicates
that higher income buyers
bid up housing
in these
predominantly residential
towns and
prices
49
are
to the higher
less sensitive
They are
taxes.
willing to
bear these taxes in exchange for preserving the residential
nature of their towns.
this hypothesis is that towns
A policy implication of
which consider the possibility of increasing their tax base
by allowing more commercial and industrial development face
property values will drop
the possibility that residential
due
to
increased
and
commercial
increase the
tax base by
Thus,
externalities.
negative
perceived
industrial
development
enough to more than
reduction in residential property
the
must
offset this
values to accomplish the
goal of enhancing the overall tax base.
Perhaps the
addition of
account for some of
with
the
other variables
which could
the perceived externalities associated
industrial development
commercial and
explanatory power
of this
model.
Also,
would enhance
the use
of
median household income in place of income per capita might
provide an even clearer relationship between income and the
willingness to pay to avoid externalities.
Finally, the use of
all
a broader database which includes
single-family properties
significance of
footage.
Such
would
probably
the physical variables,
a modification
model's simulation
prospective homebuyers.
50
the
especially square
would serve to
of the behavior
add to
improve the
of a greater
array of
APPENDIX I
Sample Correlations
Prepared by:
Marc A. Louargand
51
Mon Jul 16
1990
Page 1
10:11:31 PM
Sample Correlations
--- ------------------------AGE
VKC
DAT
.0165
-. 2844
.0618
.9828
336)
( 336)
C336)
336)
.2585
.7632
.0000
.0000
UBn
OBS
1.0000
( 336)
.0000
.9828
336)
.0000
(
(
-. 2844
336)
.0000
PRC
(
1.0000
336)
.0000
(
-. 2959
336)
.0000
1.0000
-.2959
C336)
C336)
.0313
336)
.5680
-. 0013
.0803
336)
.1420
-. 2537
.0000
.0000
.0165
C336)
.7632
C336)
.9818
.0313
(336)
.5680
LA
.0667
C 336)
.2229
.0803
(336)
.0735
336)
.1420
.1790
-. 0013
336)
.9818
-. 2537
336)
-. 0603
336)
.0000
.2705
1. 0000
.0000
-. 0446
336)
.4 154
C336)
-. 0446
336)
.4 154
1.0000
336)
.0000
-. 0456
336)
.4046
.0194
-. 0456
C336)
.0194
.7225
(
.0618
336)
.2585
(
.0667
336)
.2229
.0735
336)
.1790
-. 0603
336)
.2705
336)
.7225
336)
.4046
-. 0065
336)
.9061
-. 0267
336)
.6261
.2150
.0230
-. 1361
-. 0190
336)
C336)
S336)
.7289
AGE
(
BDRMS
(
-. 0585
336)
.2847
-.
1276
336)
.0193
(
FIRPC
1930
336)
.0004
-
.0423
336)
.4398
EDPC
-
(
.2058
336)
.0001
.0000
0566
.0224
-. 0155
.1907
C336)
C336)
C336)
.336)
S336)
.0004
.9431
-. 0341
-. 2929
C336)
C336)
.0000
-. 0643
C 336)
6
-.
.6828
.3012
.3856
336)
.0000
-. 1534
336)
.0048
.2882
0336)
.0000
.7769
.5336
.2144
.0022
-. 0220
336)
.6875
-. 1256
336)
-. 0842
C336)
.4668
336)
.0000
.0686
336)
.2094
-. 0720
336)
.0069
336)
.9000
-. 1667
.0445
1730
336)
.0015
nte)
plecie
(sameff
Co
siz
52
.239
C336)
-. 1097
-.
0039
.2317
336)
.0000
-.0803
336)
.1419
-. 0679
336)
.0003
C336)
-.
S336)
.0897
C336)
-. 1953
.0125
.0033
336)
.9513
.2133
C336)
.0000
-.
S336)
1.0000
C 336)
.6741
S336)
(
.0000
.0001
.2517
POI.PC
C336)
.0001
sie
.1006
C336)
.0213
.0761
.164 1
.0176
.7478
336)
.1233
Mon Jul 16
10:11:31 PM
1990
Page 2
POPC
----FIRPC
1930
-. 0423
.0000
.0004
.4398
.2882
-. 1953
POLPC
TXRT
voo
BDRS
-. 0585
LS
-. 0065
336)
(
C 336)
-.0566
-. 1534
-. 0267
(
.0224
.0230
-. 0190
(
TXRT
.5336
.1006
.2144
-. 2929
.0033
336)
.9513
336)
(
.0000
0039
-. 0643
336)
.2396
.0761
C336)
C336)
.2317
C336)
.0000
C336)
.0022
-
.0220
336)
.6875
-. 1256
336)
.02 13
.0176
336)
.7478
-. 0842
-. 0076
336)
.8897
.1070
336)
.04 99
-. 0332
336)
.5438
.0970
336)
.1233
.7289
1.0000
336)
.0000
.0205
336)
.7090
.0205
1.0000
336)
C336)
.7090
.0000
.0578
.1036
1.0000
-. 0059
-. 1164
.1415
.0578
.0000
.9139
.0329
.0292
336)
.5933
.0640
S336)
0
-. 1372
C336)
336)
.0804
C336)
.1415
.1036
(336)
C336)
.1641
.0640
C336)
.2419
-. 0687
C336)
.2089
C336)
C336)
-. 0059
1.0000
.2419
.2089
.9139
.0000
-. 1599
336)
.0033
-. 0076
-. 0332
-. 1164
1.0000
336)
C336)
-. 1599
C 336)
.8897
.5438
.0329
.0033
.0000
.1070
.0970
336)
.0759
C336)
.0292
336)
.0499
.2165
C336)
.0188
S336)
336)
.0001
.7311
-----------------
----------
---------------
---------------
.0897
C336)
(
---------------
C336)
-. 0679
336)
-. 0341
(
-.0697
FIRPC
EDPC
-. 1667
.336)
336)
(
POLPC
-. 0803
336)
336)
.9431
.0804
(
.2133
.3856
.0004
-.
C 336)
BDRMS
336)
(
.0125
(
.0003
.0001
.1907
336)
(
.0000
.0000
.7769
1097
.0048
.6828
336)
-.
.0445
.1419
-. 1361
AGE
C336)
C336)
C336)
C336)
(
.6741
C336)
C336)
-. 0155
336)
-.
C336)
.0001
(
.2517
C336)
C336)
.3012
.6261
S336)
DAT
.0193
C336)
336)
.2150
PRC
-.1276
C 336)
.2847
.9061
=A
C336)
(336)
336)
.0759
-. 5141
.000
.336)
336)
.0118
-. 1372
.5933
-. 5141
336)
.0000
1.0000
336)
.0000
.0288
336)
.5983
.4721
336)
.0000
.2368
336)
.0118
336)
.0000
-. 3273
S336)
0
.000
1990
Mon Jul 16
Page 3
10:11:31 PM
a--------------------OBS
(
TAN
-. 2058
336)
.0001
-.
(
PRC
.0015
.0000
.4668
.0499
336)
.3623
(
.0686
-. 0417
336)
S336)
.2094
.0720
.5336
.6625
-. 1534
-. 2576
-. 0519
.0000
.0048
.0000
.3431
-. 1230
336)
.0188
336)
.7311
.0288
336)
(
TINT
C336)
C336)
.1544
.1243
1095
-. 2752
POLPC
.2286
-. 0993
.0692
.0448
.0000
.0247
336)
.6517
-. 0244
-. 0394
.6558
.47 12
.1949
.2116
336)
.0001
.2862
336)
.0000
.0306
336)
.5768
-. 0687
.0259
336)
.6359
.4721
.0003
336)
.9953
.0000
-
.3273
336)
.0000
1.0000
336)
.0000
(
336)
.5690
336)
.0840
.3957
.5983
.2368
(
.0779
.6739
.4466
.0290
.0000
.0230
C336)
.0842
336)
.1234
.8247
336)
(
.5807
C336)
.0465
C336)
-. 0312
(
.4746
C336)
(336)
.0000
336)
BDRMS
C336)
.0000
.1191
.0001
C336)
C336)
.0242
336)
.2165
C336)
.0000
-. 0121
C336)
DIST
-. 0341
.0005
.0000
.9000
INCPC
-. 2623
C336)
.1880
(
1879
336)
C336)
(
-.
.0000
.0420
336)
.4425
S336)
EDPC
(
C336)
.0069
FIRPC
.5931
S336)
-
SAT
OTHPC
.3376
-
S336)
.0000
DAT
AGE
1730
336)
336)
(
Iyns---c--SAT-
DBTPC
-. 3192
336)
.0000
EDC
C336)
-.
C336)
C336)
C336)
.2093
.0003
-.1297
336)
.0174
-. 0134
.336)
.0575
.336)
.2933
.0256
336)
.6402
-. 1462
.0409
336)
.4547
C336)
.1513
-. 0693
.0055
336)
.2048
336)
.0073
.8062
.6884
.5036
336)
S336)
0
.1011
.0000
.000
336)
.0004
C336)
.0641
-. 0214
336)
.6955
-. 0716
336)
.1903
-. 5773
-. 4060
-. 2389
.2415
-.
1923
336)
.0000
.0000
C336)
.1018
336)
.0624
.9476
.9034
C336)
(336)
.0000
------------------
----------------------------------
--------------------
54
C336)
C336)
.6647
336)
.0000
.8376
336)
.0000
336)
S336)
.0000
.0000
336)
.0000
-. 0039
336)
.9431
-.
1449
336)
.0078
.5767
6)
S33
.0000
.3573
6)
S33
.0000
Mon Jul 16
1990
Page 4
10:11:31 PM
-------
---------------------
ASVAL
TOTEXPPC
-.
.3445
aBS
336)
(
(
.0006
.0000
-.
.4144
TWN
336)
(
.0004
.7076
.1145
336)
(
336)
(
.0000
.0358
.0627
.0603
DAT
336)
(
336)
(
.2518
.2706
-.
.0554
AGE
336)
(
.0008
.0445
.1028
336)
(
336)
(
.4165
.0597
.3641
.0571
LS
336)
(
336)
(
.0000
.2964
BDRZ4S
-.
.0219
0975
336)
(
336)
(
.6895
.0743
-.
BA
.3351
1283
336)
(
336)
(
.0000
.0186
.2653
.7757
TXRT
336)
(
336)
(
.0000
.0000
-.
.1752
POLPC
336)
(
-.
(
.9637
-.
6375
336)
(
336)
.0000
336)
.5338
.6273
(
1407
.0098
.0000
EDPC
0025
336)
(
.0013
FIRPC
1827
336)
(
.3115
LA
1928
336)
(
.0000
PRC
1853
336)
(
336)
.0000
55
Mon Jul 16
1990
10:11:31 PM
Page 5
Sample Correlations
------------------------------------------------------------------------OBS
TWN
PRC
DAT
AGE
LA
DBTPC
-. 3192
-. 3376
.0499
-. 0417
.2286
-. 0121
( 336)
336)
( 336)
336)
336)
336)
.0000
.0000
.3623
.4466
.0000
.8247
OTHPC
.5931
(
336)
.0000
SAT
(
INCPC
(
.6625
(
-. 1534
-. 2623
-. 2576
336)
336)
.0048
336)
.5336
(
.3445
336)
TOTEXPPC
.0000
ASVAL
-. 1853
(
336)
.0006
Coefficient
(
.4144
(
-. 1928
336)
(
(sample size)
336)
.0358
(
.0000
-. 0993
336)
.0692
.0247
336)
.6517
.0779
336)
-. 1095
336)
-. 0244
.0840
-. 2752
336)
.0000
336)
.1243
336)
.2706
.0627
(
336)
.2518
significance level
336)
.6558
.0448
.0603
(
.7076
336)
336)
.1234
.1544
.1145
336)
.0000
.0004
336)
336)
.6739
.4425
.1191
336)
.0290
.0842
(
.0230
(
.0420
336)
336)
.3957
.0000
-. 0519
336)
.3431
(
.5807
(
.0000
-. 0341
(
.4746
336)
.0000
336)
.0000
DIST
336)
.0242
.0000
-. 1879
336)
.0005
.0465
-. 1230
336)
(
-. 0394
(
336)
.4712
.0554
.1028
336)
C 336)
.3115
.0597
-. 1827
336)
.0008
C 336)
.4165
.0445
Mon Jul 16
DBTPC
1990
10:11:31 PM
LS
.0306
( 336)
.5768
OTHPC
(
SAT
-. 0687
336)
.2093
Page 6
BDRMS
.0259
( 336)
.6359
(
.1949
( 336)
.0003
INCPC
.2116
(
DIST
(
TOTEXPPC
336)
.0001
.2862
336)
.0000
.0571
(
ASVAL
336)
.2964
(
.3641
(
336)
.0000
(
.5690
-. 1462
336)
( 336)
.0174
.0073
-. 0134
.0409
336)
.8062
336)
336)
.2933
.0256
(
C 336)
-. 1297
.0575
(
BA
336)
.6402
-. 0975
336)
.0743
TXRT
.0003
-. 0312
.4547
(
.6647
C 336)
.0000
(
-. 0693
C 336)
.2048
(
-. 1283
.0186
336)
.0000
.0004
.1011
(
336)
.0641
-. 0214
336)
C 336)
.0000
.6955
-. 1449
-. 0039
336)
.9431
.3351
.2653
C 336)
C 336)
.0000
(
FIRPC
-. 0716
336)
.1903
-. 5773
336)
.0000
-. 4060
336)
.0000
-. 2389
336)
.0000
336)
.0078
.5767
336)
.0000
.1752
336)
.0013
-. 6375
336)
.0000
-. 0025
-. 1407
336)
.0098
(
.7757
336)
.0000
336)
.0000
336)
.5036
.0219
.6895
-. 1923
(
.6884
(
.1513
336)
.0055
C 336)
336)
.9953
POLPC
.8376
( 336)
.0000
336)
.9637
Mon Jul 16
DBTPC
1990
10:11:31 PM
EDPC
.2415
( 336)
.0000
OTHPC
(
SAT
.1018
336)
.0624
Page 7
DBTPC
1.0000
(
INCPC
(
DIST
(
TOTEXPPC
ASVAL
336)
.0000
336)
.0000
.1761
.0000
336)
.0012
.3573
-. 1603
336)
.0000
336)
.0032
.6273
336)
.0000
.0063
336)
336)
.0050
(
.2638
336)
.0000
.0012
DIST
-. 1603
(
-. 0645
(
1.0000
336)
.0000
.8928
336)
.0000
(
(
.8928
336)
.0000
1.0000
336)
.0000
(
336)
(
.3177
336)
.0000
.8077
336)
.0000
(
.7123
336)
.0000
.0000
(
336)
.2386
.0019
336)
.7398
(
.5296
(
336)
.0000
(
.2386
336)
.0032
-. 1686
(
-. 0182
(
INCPC
.1761
336)
336)
-. 1686
(
.0546
336)
.3182
(
-. 0645
(
.9090
(
336)
.2638
336)
.0000
.0050
336)
SAT
.1528
1.0000
(
336)
.9034
336)
.0000
336)
.0000
.1528
(
.5338
(
336)
.0000
-. 4093
(
.9476
(
OTHPC
-. 4093
336)
.0019
.3177
336)
.0000
.2915
336)
.0000
.2915
336)
.0000
1.0000
336)
.0000
.4049
336)
.0000
.0188
336)
.7311
.5956
.0315
336)
C 336)
.0000
.5651
Mon Jul 16
DBTPC
1990
10:11:31 PM
Page 8
TOTEXPPC
.0063
(
336)
(
.9090
OTHPC
336)
.0000
SAT
-.0182
(
336)
.5296
(
.0000
INCPC
336)
.0000
DIST
.5956
(
.0188
(
336)
.7311
TOTEXPPC
336)
.0000
ASVAL
336)
.0000
336)
.5651
.2487
(
336)
.0000
.2427
(
336)
.0000
.0315
(
1.0000
(
336)
.0000
.4049
(
336)
.7398
.7123
(
336)
.3182
.8077
(
ASVAL
.0546
1.0000
(
336)
.0000
APPENDIX II
List of Towns in Sample
List of Towns in Sample
Arlington
Bedford
Framingham
Lexington
Malden
Natick
Wakefield
Waltham
Wayland
Woburn
REFERENCES
1.
Banker and Tradesman Real Estate Data Publishing,
Banker and Tradesman 1989 Annual, Middlesex North and
Middlesex South, Boston, MA, 1990.
2.
Goodman, Allen C., "Hedonic Prices, Price Indices and
Housing Markets," Journal of Urban Economics, Vol.
5,
1978, pp.
471-484.
3.
Griliches, Zvi, ed. Price Indexes and Quality Change,
Harvard University Press, Cambridge, MA, 1971, ch.
1.
4.
Hamilton, Bruce W., "Zoning and Property Taxation in a
System of Local Governments,"
Urban Studies, Vol.
12,
1975, pp. 205-211.
5.
Hamilton, Bruce W.,
"Property Taxes and the Tiebout
Hypothesis: Some Empirical Evidence," in Fiscal Zoning
and Land Use Controls, Edwin S. Mills and Wallace E.
Oates, eds.,
D.C. Heath and Company, Lexington, MA,
1975, ch. 2.
6.
Hyman, David N. and E.C. PasourJr.,
"Real Property
Taxes, Local Public Services, and Residential Property
Values," Southern Economic Journal, Vol.
39, 1973, pp.
601-611.
7.
Ihlanfeldt, Keith R., "Property Taxation and the Demand
for Housing: An Econometric Analysis," Journal of Urban
Economics, Vol.
16, 1984, pp.208-224.
8.
Kohlepp, Daniel B. and Charles A.
Ingene, "The Effect
of Municipal Services and Local Taxes on Housing
Values," AREUEA Journal, Vol.
7, 1979, pp. 318-343.
9.
Louargand, Marc A., "Sample
with data from this sample
Appendix I.
Correlations,"
prepared
and included herein as
10. McMillan, Melville and Richard C. Carlson, "The Effects
of Property Taxes and Local Public Services upon
Residential Property Values in Small Wisconsin Cities,"
American Journal of Agricultural Economics, February,
1977, pp. 81-87.
11. Oates, Wallace E., "The Effects of Property Taxes and
Local Public Spending on Property Values: An Empirical
Study
of
Tax
Capitalization
and
the
Tiebout
Hypothesis,"
Journal of Political Economy, Vol.
77,
1969, pp. 957-971.
12. Oates, Wallace E., "The Effects of Property Taxes and
Local Public Spending on Property Values: A Reply and
Yet Further Results," Journal of Political Economy,
Vol. 81, 1973, pp. 1004-1008.
13. Pollakowski, Henry 0.,
"The Effects of Local Public
Spending on Property Values: A Comment and Further
Results," Journal of Political Economy, Vol. 81, 1973,
pp. 994-1003.
14. Steinway, Susan, "How Your School System Stacks Up,"
(tables included within "Private Lives, Public Schools"
by Margaret Pantridge) Boston Magazine, September,
1989, pp. 144-145 and 184.
15. Sullivan, Arthur M., Urban Economics, Richard D. Irwin,
Inc., Homewood, IL and Boston, MA, 1990, ch.13.
16. Tiebout,
Charles M.,
"A Pure
Theory of
Local
Expenditures," Journal of Politcal Economy, Vol. 64,
1956, pp. 416-424.
17. Universal Publishing Co.,
Inc., Universal Atlas of
Metropolitan
Boston
and
Eastern
Massachusetts,
Stoughton,
MA, 1988.
(includes U.S.
Dept. of
Commerce, Bureau of Census data for 1985 income per
capita of towns in sample).